People engine optimization

ABSTRACT

Some embodiments promote website credibility and the optimization of websites for people by automatedly quantifying various elements of a website into component credibility scores. In some embodiments, a set of encoded credibility scoring rules are used to compute each of the component credibility scores, wherein the credibility scoring rules are derived based on factors that have been identified by a grouping of people that preferably represent a primary demographic of users that consume the content of a particular classified type of website. In some such embodiments, the credibility scoring rules are derived from commonality that is identified from a sample set of known credible and/or non-credible websites of a particular classification. Once the credibility scoring rules are defined, the system applies the rules to other websites having the same classification as those from which the rules are derived to automatically generate credibility scores for the other websites.

CLAIM OF BENEFIT TO RELATED APPLICATIONS

This application is a continuation of the U.S. nonprovisional patentapplication Ser. No. 13/896,125 entitled “People Engine Optimization”filed on May 16, 2013 which is a continuation of the U.S. nonprovisionalpatent application Ser. No. 13/736,276 entitled “People EngineOptimization” filed on Jan. 8, 2013, now U.S. Pat. No. 8,468,028, whichis a continuation of the U.S. nonprovisional patent application Ser. No.13/486,873 entitled “People Engine Optimization” filed on Jun. 1, 2012,now U.S. Pat. No. 8,374,885, which claims the benefit of U.S.provisional application 61/492,102, entitled “People EngineOptimization”, filed Jun. 1, 2011. The contents of application Ser. Nos.13/896,125, 13/736,276, 13/486,873 and 61/492,102 are herebyincorporated by reference.

TECHNICAL FIELD

The present invention pertains to a system, methods, and softwareproducts for determining credibility of websites.

BACKGROUND

Internet content is a mixture of informative, artistic, entertainment,and for profit content. One of the primary benefits of the Internet isthat anyone can quickly, easily, and economically create content that ishosted and served to others in the form of one or more websites.However, this content can also be intermixed with false information,spam, malware, adware, and other elements that are intended to defraud,harass, deceive, or otherwise mislead content consumers. It can bedifficult for a user that is a content consumer to distinguish betweencredible and non-credible content. As a result, the user may be misledinto buying a good or service that it does not want or is different thanthe content consumer's expectations, provide confidential information toa non-credible entity that can then misappropriate that information fornefarious purposes, or the user may simply consume information that isrepresented as truthful and accurate, but is instead falsified ormisrepresented.

The burden of distinguishing between credible and non-credible websitesis mostly left to the user. Some users identify a credible website thathosts credible content as one that is authoritative or a primary sourcefor the content that it distributes. Some examples of authoritative orprimary source content creators are sources like www.cnn.com,www.microsoft.com, and www.uspto.gov. Some users identify a crediblewebsite as belonging to an established and trusted business or one thatoffers goods and services from credible sources (i.e., well known andestablished dealers, manufacturers, service providers, etc.). Forexample, users that purchase goods from www.apple.com are assured thatthe Apple® products they purchase made and warranted by themanufacturer. Still some users identify a credible website based on theamount of spam, malware, adware, and the like that is present on such awebsite. The more banner advertisements and pop-ups, the more likely thewebsite is one that is not credible. In any of these and other cases,the credibility of a website is based on the knowledge and experience ofthe user. Less Internet savvy users are more likely to be duped by thenon-credible websites and are thus more prone to fraud, misappropriationof confidential information, and consumption and dissemination offalsified or inaccurate information.

Some automated tools currently exist to aid better aid the user ingauging the credibility of a website. One such tool is the searchengine. Search engines such as Google, Bing, and Yahoo, identifywebsites that are of potential interest to a user based on one or morequery parameters provided by the user. The search engine ranks thewebsites that match a user query based on relevancy factors. Theserelevancy factors account the closeness of the user's query parametersto words that appear in a website and a website's popularity asdetermined by the number of incoming links to the website as someexamples. However, these relevancy factors and the search enginerankings that are derived from the relevancy factors usually do notaccount for credibility. As a result, some users incorrectly assume thatthe highest ranked websites (i.e., first presented websites in thesearch engine results) not only provide the most relevant content, butalso provide content that is trustworthy, accurate, and credible. Someusers also assume that the first few presented search engine results areusually authoritative or are the primary source of the content that theydistribute and that the distributed content is spam-free.

Besides the fact that the search engine rankings do not account forwebsite credibility, the rankings can also be manipulated such that anon-credible website will appear higher in the rankings, thereby causinga user to improperly perceive that website as being more credible thanit is. Search engine manipulation is the byproduct of abuses in searchengine optimization. More specifically, non-credible websites can beoptimized with content, keywords, links, etc. such that they are rankedhighly when a user searches for certain keywords even though thewebsites may in fact have little to do with the searched for keywords orthe websites are relevant to the search for keywords, but contain spam,are intended to defraud, or contain inaccurate or falsified information.In summary, search engine optimization can be used to make a websitethat is irrelevant, full of spam, or that contains other non-crediblecontent to appear in the search rankings to be more relevant than it isand, as a result, appear to some users as being more credible than itis.

Search engine optimization can also have the effect of making crediblewebsites appear to be less credible. For instance, a website creator mayrepeat various keywords unnecessarily, create extraneous content, andperform other optimizations that improve the website's ranking in thesearch engines, but that pollute the website with confusing andunnecessary information that makes the desired for content hard to find.Such a website can be perceived as being less credible when the soughtafter content is hard to find, surrounded by unnecessary text (e.g.,repeated words or phrases), hyperlinks, or visual elements, and thisunnecessary text, hyperlinks, and visual elements are needed to improvethe website's rankings in the various search engines. Stateddifferently, search engine optimization results in websites that areoptimized for search engines and not for the people that consume thecontent from those websites. As a result, the subjective criteria usedby people to gauge the website's credibility is sometimes ignored orleft to be a secondary concern for search engine rankings or searchengine optimized websites.

A further shortcoming of using search engine results as an indicator forwebsite credibility is the fact that some search engines do not considerthe amount of “spam” elements on the website when ranking the website.For instance, a particular website may be the highest ranked websitebecause of the amount of content it contains relating to a particularsubject and because of the number of links that point to that particularwebsite. However, this same website may be littered with banner ads,annoying flashing graphics unrelated to the primary content, poorcontrast between text and background images that make the actual textdifficult to read, large videos or graphics that increase the downloadtime for the website, pop-ups, etc. When a user visits such a websiteand is bombarded with these and other spam elements, the user mayimmediately identify the site as non-credible. Consequently, the user isless likely to complete a commercial transaction at that websiteresulting in financial loss to the website. Also, the user is lesslikely to remain at the website to consume content or become interestedin advertising or other promotions of the website. These and otherfactors highlight the importance of not only having a relevant website,but one that is also perceived as being credible.

Today, review websites exist to assist a user in ascertaining thecredibility of a website. At these review websites, users rate a websiteand express their opinions about that website such that others canascertain the credibility of a website based on the experiences ofothers. However, the problem with understanding credibility through thisapproach is that the credibility data is at a third party site.Therefore, the user must first lookup a website of interest at the thirdparty site in order to ascertain that website's credibility beforeaccessing the website. Another shorting coming of such review websitesis that the credibility data at these websites is not derived using thesame set of rules or criteria for all websites that are similarlyclassified. For example, an overly critical reviewer may find fault withan irrelevant feature of a first website and an overly sympatheticreviewer may ignore a glaring issue of a second website. A small set ofonly negative reviews may also fail to adequately convey the credibilityof a website. The reviews may come from users that are not from theprimary demographic to which the website caters to. Accordingly, usersubmitted reviews cannot be used to accurately gauge the credibility ofa website. More importantly, the subjectivity and inconsistent samplingof reviews does not allow a website administrator or user tocomparatively gauge the credibility of one website relative to othersimilarly classified websites.

Accordingly, there is a need to better promote website credibility sothat the content that is placed on the Internet is optimized for people.To promote people optimized websites, there is a need to automatedlyidentify and quantify factors that people use to gauge credibility. Suchfactors extend beyond the relevancy of the content and include thepresentation of the content as well as the accuracy, trustworthiness,and safety of the content being presented. There is a need to providethe identified and quantified factors to website administrators so thatthey may appreciate the website elements that beneficially anddetrimentally affect their websites' credibility and so that theadministrators can take directed action to better optimize thecredibility of their websites. There is also a need to better enableusers to identify credible websites from non-credible websites. In sodoing, users are provided a better online experience and are protectedfrom non-credible sites.

SUMMARY OF THE INVENTION

It is an objective of the present invention to define a system, methods,and computer software products to promote website credibility and theoptimization of websites for people. It is an objective to automatedlyquantify various elements of a website into component credibility scoresfrom which an overall credibility score for the website is derived. Itis objective to automatedly derive the component credibility scoresbased on factors that people (constituting a primary demographic of thecontent consumers for that website) have identified to be ofsignificance when gauging the website's credibility. Moreover, it is anobjective that the set of identified factors be encoded into a set ofrules. The set of rules can then be applied to a set of websites thatare within a particular classification in order to produce credibilityscores for each website in the set of websites, wherein the credibilityscores for the set of websites is computed based on the same set offactors, thereby producing standardized and normalized credibilityscores that can be used for comparative analysis.

In some embodiments, the credibility scores (i.e., overall andcomponent) are provided to website administrators so that theadministrators may identify those website elements that beneficially anddetrimentally affect their websites' credibility. In response, thewebsite administrators may perform credibility optimizations to theirwebsites. Such optimizations improve the credibility of the websites byimproving user perception of the websites. Consequently, a user is morelikely to remain on the website, thereby increasing the likelihood ofthe user completing a commercial transaction through the website orincreasing the likelihood that the user relies on the website foraccurate and trustworthy content.

In some embodiments, the credibility scores are provided through atoolbar or via web browser functionality to users that want ascertainthe credibility of a website prior to visiting the website or whilevisiting the website. In some embodiments, the credibility scores areused to reorder traditional search engine ranking results such that theordering accounts for the credibility as determined by the system andmethods described herein in addition to or instead of the relevancyfactors ordinarily utilized by search engines to rank websites.

To achieve these and other objects, some embodiments provide a peopleengine optimization (PEO) system. The PEO system computes credibilityscores for different websites to quantify their credibility based onpeople identified credibility factors. The credibility scores include anoverall credibility score that is derived from various componentcredibility scores. Each component credibility score quantifies thecredibility that is associated with a particular factor of a website asembodied by one or more elements of the website.

In some embodiments, the PEO system utilizes a set of encodedcredibility scoring rules to compute each of the component credibilityscores. In some embodiments, the credibility scoring rules are derivedbased on factors that have been identified by a grouping of people thatpreferably represent a primary demographic of users that consume thecontent of a particular classified type of website. However, it shouldbe apparent that the grouping of people can include any sampling ofusers. Specifically, the grouping of people is presented a sampling ofwebsites for the particular classified type of website. For example,when the particular classified type of website is an e-retailer (i.e.,online store), the grouping of people may be presented with a samplingof sites such as www.amazon.com, www.buy.com, and www.walmart.com. Thegrouping of people analyzes the websites to identify factors fordifferent website elements that beneficially or detrimentally impact thecredibility of the websites. Some such factors include stylizationfactors such as coloring, fonts, sizes, and number of advertisements.The grouping of people provides a weight to each identified factor. Theweight quantifies how much of an effect the identified factor has on theoverall credibility of the website as perceived by the user identifyingthe factor. The PEO system obtains a listing of the identified factorsand analyzes the factors for commonality. Any factor that has beenidentified and weighted similarly by a threshold number of people isencoded into a credibility scoring rule. In encoding a credibilityscoring rule, the PEO system defines an algorithm for automatedlyquantifying the factor that is associated with a particular websiteelement into a component credibility score. The credibility scoring rulecan then be automatically applied to other websites with the sameparticular website element in order to compute a credibility componentscore for each such website. By applying the same credibility scoringrule to different websites, the PEO system is able to compute astandardized credibility component score for all such websites that isunaffected by individual biases or inconsistent interpretation. In thismanner, the credibility scoring rules are derived using a judgmentalapproach.

In some embodiments, the PEO system derives the credibility scoringrules using an empirical approach. In some such embodiments, thecredibility scoring rules are derived from commonality that isidentified from a sample set of known credible and/or non-crediblewebsites of a particular classification. The sample set of knowncredible websites of a particular classification are identified based onaggregated positive reviews, website popularity, etc. The identifiedsample set of known credible websites of a particular classification areprogrammed into the PEO system for analysis. Next, the PEO system crosscompares the identified websites to identify commonality between theidentified websites. Specifically, commonality is identified when asufficient number of the identified websites include the same or similarwebsite elements. Commonality between websites of a sample set of knowncredible websites identifies one or more website elements that benefitwebsite credibility for websites of the same particular classificationas the sample set. Similarly, commonality between websites of a sampleset of known non-credible websites identifies one or more websiteelements that are detrimental to website credibility for websites of thesame particular classification as the sample set. The PEO system mayinclude various visual matching routines and website crawlers toautomate the identification of commonality. PEO system administratorscan also manually identify the commonality between the sample set ofwebsites. The identified commonality is then encoded to a credibilityscoring rule. The credibility scoring rule is then applied to otherwebsites of the particular classification as the sample set of websites.In so doing, the PEO system automatically computes a componentcredibility score for the other websites, wherein the computedcredibility component score is standardized because it is derived fromthe same rules for all websites, thereby eliminating individual biasesor inconsistent interpretation.

Once the credibility scoring rules are defined using either thejudgmental or empirical approaches described above, the PEO systemapplies the rules to other websites having the same classification asthose from which the rules are derived. The different sets of rules arederived because different factors play into the credibility fordifferently classified websites. For instance, a news website will bedeemed credible based on different factors than a video game website. Tocompute the component credibility scores and the overall credibilityscore for a website based on the defined credibility scoring rules, awebsite is first retrieved by the PEO system and parsed into itselements. The website is classified. In some embodiments, classificationinvolves identifying a primary demographic of users for the website.Based on the classification, a set of credibility scoring rules relevantto the website classification are retrieved. The appropriate parsedelements are passed as inputs to the set of credibility scoring rulesand different component credibility scores are computed for some of theelements. From each component credibility score derived for a particularwebsite, an overall credibility score is computed.

To complement the computed credibility scoring rules, the PEO system mayalso incorporate third party data that identifies credibility of awebsite. For example, the PEO system may aggregate the number ofFacebook “likes” for a particular website and use that information inthe computation of a component credibility score that is accounted forin the website's overall credibility score.

In this manner, the credibility of different is automatedly derived.Since the same set of credibility scoring rules are applied to similarlyclassified websites, the credibility scores can be comparativelyanalyzed and reference to other websites can be made in order toprecisely determine what constitutes a credible element and anon-credible element.

In some embodiments, the PEO system provides the component credibilityscores to website administrators. In so doing, the PEO system providesthe website administrators with targeted insight about which elementsbeneficially or detrimentally impact the credibility of theadministrator's website. Based on this information, the administratorcan take targeted action to improve website credibility.

In some embodiments, the PEO system provides the component credibilityscores to users that are content consumers consuming content presentedat various websites. In so doing, the PEO system provides an unbiasedand automated system to notify users as to which websites are credibleor non-credible. Consequently, users have a more enjoyable web browsingexperience and are less likely to be subjected to spam, fraud, ormisinformation. Moreover, users are provided the credibility scores asthey browse the web without the need to read reviews and ratings on thecredibility of a website at a third party site before accessing thatwebsite. To facilitate such a user browsing experience, some embodimentsprovide the credibility scores through a toolbar application that runsin conjunction with a web browser application. Whenever, the web browserpoints to a new website, the toolbar automatically queries the PEOsystem for the credibility score that is associated with that website.The credibility score is presented in the toolbar as the website loadson the web browser application. The credibility score can also be usedto ensure a safe browsing experience. Specifically, when the credibilityscore for a particular website falls below some threshold value, thetoolbar can halt the loading of the particular website until the userconfirms that he/she is aware of the low credibility score of theparticular website and that the user wishes to continue loading theparticular website. In some embodiments, the credibility scores areintegrated with search engine results such that when a pointing toolhovers over a search engine result, the credibility score that isassociated with the website represented by that result is presented. Insome embodiments, the credibility scores are used to reorder searchengine results. In some such embodiments, a user performs a searchengine query. The results from the search engine are intercepted by thePEO system and reordered according to the credibility scores associatedwith each of the websites returned by the search engine.

BRIEF DESCRIPTION OF THE DRAWINGS

In order to achieve a better understanding of the nature of the presentinvention a preferred embodiment of the People Engine Optimizationsystem and methods will now be described, by way of example only, withreference to the accompanying drawings in which:

FIG. 1 presents a process for determining the credibility of a websitein accordance with some embodiments.

FIG. 2 presents components of the PEO system in accordance with someembodiments.

FIG. 3 presents a first process implementing a judgmental approach todefining credibility scoring rules in accordance with some embodiments.

FIG. 4 presents a second process implementing an empirical approach todefining credibility scoring rules in accordance with some embodiments.

FIG. 5 illustrates presenting credibility scores to a particular websiteadministrator in accordance with some embodiments.

FIG. 6 illustrates a toolbar within a browser window for providingcredibility scores to users in accordance with some embodiments.

FIG. 7 illustrates using “mouse-over” functionality to presentcredibility scores in accordance with some embodiments.

FIG. 8 illustrates reordering search engine results based on credibilityscores in accordance with some embodiments.

FIG. 9 illustrates a computer system with which some embodiments areimplemented.

DETAILED DESCRIPTION OF THE INVENTION

In the following detailed description, numerous details, examples, andembodiments of a People Engine Optimization (PEO) system and methods areset forth and described. As one skilled in the art would understand inlight of the present description, the system and methods are not limitedto the embodiments set forth, and the system and methods may bepracticed without some of the specific details and examples discussed.Also, reference is made to accompanying figures, which illustratespecific embodiments in which the invention can be practiced. It is tobe understood that other embodiments can be used and structural changescan be made without departing from the scope of the embodiments hereindescribed.

I. Overview

Website credibility is difficult to quantify, because it is primarilypredicated on subjective factors. Moreover, these subjective factorsdiffer from one type of website to another based on the preferences ofthe people that primarily access the websites. For instance, the factorsthat make a shopping website (i.e., e-retailer) credible are differentthan the factors that make a business informational website (i.e.,homepage) or news website credible. In any case, website credibility isone of the primary forces driving traffic to a website and keepingtraffic at the website. A credible website is one that users feelcomfortable interacting with, obtaining information from, and providinginformation to including providing financial and confidentialinformation. Stated differently, a credible website is one that containsfew or no spamming elements, does not defraud, and clearly and directlyprovides accurate and trustworthy information. Examples of some otherfactors driving traffic and keeping traffic at the website include therelevancy, value, and timeless of information that is presented at thewebsite.

It is important for website administrators to be able to understandtheir websites' credibility and, more importantly, to be able tooptimize the credibility of their websites. Understanding websitecredibility helps explain certain trends in user access to a website.For example, why users view a homepage but not other pages that arelinked to from the homepage or why a website attracts a particulardemographic of users but not other demographics of users. Afterunderstanding website credibility, the website administrator can thenoptimize the site on the basis of credibility. This optimization isreferred to herein as People Engine Optimization (PEO). A peopleoptimized website attracts new users while keeping existing users betterengaged.

It is also important for users to understand website credibility.Understanding website credibility allows a user to avoid websites thatperpetrate fraud, avoid websites that contain lots of spam, avoidwebsites that disseminate falsified or inaccurate information, and avoidwebsites that sell goods or services that misrepresent the true originor quality of the goods or services. Additionally, users that are ableto distinguish between credible and non-credible websites will be lesslikely to have their confidential information stolen or misappropriatedand will have a more enjoyable and efficient web browsing experience asthey will be able to quickly access the information, goods, or servicesthat they seek.

To meet these objectives, some embodiments provide a People OptimizationEngine (PEO) system and methods that automatedly analyze differentwebsites and compute credibility scores for those websites based onsubjective factors that have been identified preferably by a primarydemographic of users for those websites. FIG. 1 presents a process 100for determining the credibility of a website in accordance with someembodiments. The process 100 is performed by the PEO system which isdescribed in detail below.

The process 100 begins by automatedly retrieving (at 110) a website forwhich one or more credibility scores are to be computed. Retrieving awebsite includes downloading a base HyperText Markup Language (HTML)page, downloading all embedded objects that are included within the baseHTML page, executing or otherwise performing scripts or applicationsthat are part of the base page, and/or rendering the website. Retrievinga website may further include downloading internally linked websites andanalyzing the aggregate set of websites. Website retrieval is ordinarilyperformed by the PEO system submitting a HyperText Transfer Protocol(HTTP) GET request to a server that hosts the website of interest. Inresponse, the server passes the HTML page, embedded objects, scripts,and applications to the PEO system using a packet based protocol such asthe Internet Protocol (IP) and preferably where a connection orientedprotocol such as the Transmission Control Protocol (TCP) facilitates areliable transfer of the HTML page, embedded objects, scripts, andapplications.

The process parses (at 120) the retrieved website into its componentelements. Parsing is performed by identifying specific delimiters withinthe website such as HTML tags as some examples. As used herein, websiteelements include any object of the website (interactive, executable,visual, or hidden), any attribute for an object, or other aspects of thewebsite that are derived from the objects. Some examples of websiteelements include graphics, advertisements, coloring, font, text,hyperlinks, scripts, interactive tools, input fields, number ofadvertisements, number of different colors, or any other object that isspecified using HTML, JavaScript, ActiveX, Cascading Style Sheets (CSS),XML, and other similar languages. The PEO system may utilize a websitecrawler or automated script to parse and identify the componentelements.

Next, the process classifies (at 130) the retrieved website.Classification is performed on the basis of various identifiersappearing within the website or its meta-data. For example, when thesports related terms repeatedly appear in the text of the website, thatPEO system can classify that website as a sports related website. Asanother example, if the same sports website includes pricing and ashopping cart option, then the PEO system can further classify thewebsite as a sports website, a shopping website, or a sports shoppingwebsite. Classification may also be performed by looking up the domainname or Uniform Resource Locator (URL) of the website in aclassification database. Classifications can be enumerated with anydesired degree of granularity. For example, a video gaming website maybe classified as an entertainment website or that same website may beclassified as an entertainment website that pertains to males age 15-35with average income of $25,000-$60,000.

Based on the classification performed at 130, the process identifies (at140) a set of credibility scoring rules that will be used to computevarious component credibility scores and the overall credibility scorefor the retrieved website. The identified set of credibility scoringrules define the elements of the retrieved website that will beconsidered in computing the credibility score for the retrieved websiteand how the credibility score will be quantified for those elements. Inthis manner, all websites of a given classification will have theircomponent credibility scores and overall credibility score computedsubject to the same set of rules such that the scores can be crosscompared.

The parsed website elements are passed (at 150) as inputs to the set ofcredibility scoring rules. As output, the set of credibility scoringrules derive various component credibility scores for the retrievedwebsite. The component credibility scores are computed on an element byelement basis such that users and website administrators can appreciateexactly which parts of the website are considered credible and whichparts of the website are considered not credible. Each componentcredibility score represents a quantification for the credibility of aparticular element of a website. Specifically, a quantification based onthe attributes defined for the particular element or a quantificationbased on the presence of the particular element. Each componentcredibility score may be represented as a numerical value, thoughalternative representations may also be used. For example, a firstcredibility scoring rule accepts as input one or more website elementsfor the font and coloring of the website with attributes of the websiteelements defining the specific font and specific coloring. Then, basedon the first credibility scoring rule, a first component credibilityscore of 7/10 for the specific font and specific coloring of the websiteis computed and presented to a user or website administrator to indicatethat the specific font and specific coloring is not considered to bedetrimental to the credibility of the website. Similarly, a secondcredibility scoring rule accepts as input one or more website elementsrelated to the number and positioning of advertisements of the website.

Then, based on the second credibility scoring rule, a second componentcredibility score of 3/10 for the number and positioning ofadvertisements appearing on the website is computed and presented to auser or website administrator to indicate that the number andpositioning of the advertisements causes the website to be considered asless credible. In other words, the credibility component score indicatesthat users are more likely to click away from that website or spend lesstime on that website as a result of the number and positioning of theadvertisements on the website, wherein the credibility score rule hasdetermined that the number and positioning of the advertisements on thewebsite is considered spamming, thereby resulting in the lowercredibility component score. The website administrator can then directlyrespond and improve its credibility by removing or reducing the size ofthe advertisements on its website. Also, users can view the first andsecond component credibility scores and ascertain that the website doesnot necessarily contain harmful content, but is replete with unnecessaryadvertisements. In summary, each component credibility score is intendedto provide a quick and easy to understand reference as to which websiteelements are beneficial to the credibility of the website and whichwebsite elements are detrimental to the credibility of the website.

The process aggregates (at 160) the component credibility scores toderive an overall credibility score for the website. Different websitesmay have different numbers of component credibility scores based on theelements of the website. Preferably however, component credibilityscores are derived for at least a basic set or standard set of elementsthat all websites include, such as coloring, fonts, number of images,number of advertisements, etc.

The process then derives (at 170) the overall credibility score for thewebsite based on the aggregated component credibility scores for thatwebsite. The overall credibility score is derived based on its parts(i.e., the component credibility scores) and provides an overallimpression as to the credibility of the website. In some embodiments,deriving the overall credibility score involves computing the averagefor all the component credibility scores. In some other embodiments,deriving the overall credibility score involves applying differentweights to different component credibility scores so that some scoresimpact the overall credibility score more so than other componentcredibility scores. The overall credibility score is also a numericrepresentation that is quick and easy to understand. The overallcredibility score and each of the component credibility scores can bepresented in a range or can include a percentage to provide acomparative reference with respect to the scores of other websites.Moreover, the scores of different websites are computed using the samescoring rules in order to enable a cross comparison of the scores. Thiscross comparison allows a user to see how the credibility of aparticular website compares to the credibility of other websites. As aresult, the scores can serve as a guide to a safer and more enjoyableweb browsing experience in which browsing is not only predicated basedon relevancy factors of websites as identified by search engines, butalso based on credibility factors including reputation, trustworthiness,etc. as identified by the PEO system.

The process stores (at 180) the overall credibility score and thecomponent credibility scores to a PEO system database for subsequentdistribution to website administrators, PEO system tools (e.g., softwaretoolbar), or third parties (e.g., search engines). The scores can beperiodically updated by executing another iteration of the process 100.The process 100 can be executed on a website whenever content on thatwebsite changes, formatting of the website changes, or on a recurringinterval basis (e.g., every month).

As noted above, the overall credibility score and the various componentcredibility scores provide several advantages to website administratorsand users or content consumers. Website administrators can utilize thecredibility scores to optimize their websites based on the preferencesof their users or content consumers. Generally, this entails optimizingthe website so that the user experience is tailored to the likes of theprimary demographic of users accessing the website. This may include,for example, making the provided content easier to see, replacingelements (e.g., fonts, coloring, images, etc.) appearing within thewebsite with elements that are preferred by users, and ensuring that thewebsite does not include an excessive number of spam elements orincludes elements preferred by the primary demographic of users (e.g.,different graphics or advertisements). To this objective, the overallcredibility score informs the website administrator as to the overallperception of the website's credibility which can be further used incomparatively assessing the credibility of the website in relation toother similarly classified websites. The component credibility scoresinform the website administrator as to specific website elements thatmost detrimentally impact the credibility of the website and that can bebetter optimized. These scores are especially useful when websiteadministrators are unaware of the impact that certain website elementshave on their website's credibility or the website administrators simplydo not have the resources or time to conduct a study to identify thepreferences of their primary demographic. In some embodiments, the PEOsystem further provides recommendations or suggestions on how a websiteadministrator can improve its website's credibility. In some suchembodiments, the PEO system identifies the recommendations orsuggestions from the credibility scoring rules. For instance, the PEOsystem may compute a low component credibility score for a particularwebsite element of a website. Then, based on the credibility scoringrule used to derive the component credibility score, the PEO systemidentifies what specific changes can be made to that particular websiteelement to improve upon its credibility. These recommendations orsuggestions can be provided for any component credibility score forwhich a credibility scoring rule is derived. Furthermore, theserecommendations or suggestions can be provided as part of a premium orpaid-for service of the PEO system.

Users can also utilize the credibility scores to better understand thecredibility of a website. This is especially useful for unknowledgeableor less experience users that have difficulty in identifying desiredcontent or often are the targets of spammers, phishing websites, and thelike. Using the credibility scores, users can ascertain whether aparticular site is credible before ever pulling up that website orengaging in further interactions with that website, such as by providingidentification, financial, or confidential information to the website.

Some website elements that can impact the credibility of a website andthat are quantified into component credibility scores by the PEO systeminclude: advertisements, graphics, color, fonts, media objects, amountof content and its affect on the load-up time of the website, howverbose or direct a website is, and placement of information (easilyaccessible or hidden). For example, a credible website may include: textthat is easily identifiable from background coloring or graphics, fontsthat are within a specified range of sizes, a limited number ofdifferent fonts, a proportional number of graphics or advertisements totext, proper layout of graphics or advertisements to text (graphics areinterspersed), content that is not hidden, does not contain trackingelements (e.g., scripts), includes a proportional number of hyperlinks,and obtains content from trusted sources. Other examples include whetherthe website identifies the principle agents or management (for abusiness website), clearly presents terms and services, clearly presentscontact information with at least one of a telephone number, streetaddress, and email address, clearly defines a refund policy or ashipping policy (for an e-commerce website), contains certifications orawards (e.g., Better Business Bureau, VeriSign Secured, etc.), andencrypts confidential information. Accordingly, credibility for somewebsite elements is computed based on attributes defined for thoseelements, whereas the credibility for some other website elements iscomputed simply based on the presence or omission of those elements fromthe website.

The above listing provides an exemplary set of factors, however itshould be apparent that what constitutes a credible website isultimately determined based on the preferences of the primarydemographic of users that access similarly classified websites. Someusers of a first website classification may prefer graphics to text,whereas users of a second website classification may prefer text tographics. More specifically, users of a gaming website will perceive agaming website as more credible when it has a large number ofscreenshots and videos, whereas users of an academic or informativewebsite will perceive an academic website as less credible when there isa disproportionate number of graphics to text. As another example,fashion related websites that primarily have the colors pink, red, andblack may be perceived by their users as being more credible than othersimilarly classified websites. As evident, these subjective factors canvary greatly between different websites and it is for this reason thatwebsite credibility has previously been difficult to ascertain. However,by tailoring the credibility scoring rules to the preferences of theprimary demographic of users for similarly classified websites, the PEOsystem can automatically and systematically produce credibility scoresthat are standardized and normalized for all websites fitting aparticular classification.

II. PEO System

FIG. 2 presents components of the PEO system 210 in accordance with someembodiments. As shown, the PEO system 210 comprises website retrievalprocess 220, analyzer 230, credibility scoring rules database 240, andcredibility score database 250. Some or all of these components 220-250are embodied as software applications or processes that reside onnon-transitory computer-readable media and that execute on one or morephysical computing devices. The components 220-250 transform generalpurpose computing resources of the computing devices to implement andperform the PEO system functionality. In other words, the computingdevices on which the PEO system 210 executes comprises general purposeprocessors, random access memory, non-volatile storage, and networkresources that are transformed by the components 220-250 into one ormore specific purpose machines that produce the credibility scores andthat provide the other PEO system functionality that is describedherein. Each of the components 220-250 may execute on separate physicalcomputing devices with independent sets of resources or as virtualmachines on a single computing device by sharing resources of the singlecomputing device or by being allocated separate partitions of theresources of the single computing device.

A. Web Retrieval Process

In some embodiments, the website retrieval process 220 is an automatedweb crawler that obtains different websites from the Internet or otherdata network from which websites are accessible. The website retrievalprocess 220 utilizes a network interface of the PEO system that providesaccess to the Internet or other data networks to retrieve the differentwebsites. The website retrieval process 220 retrieves different websitesusing standardized messaging protocols (e.g., IP, TCP, HTTP, etc.).

In some embodiments, a configuration file is provided to the websiteretrieval process 220 to specify the time and URLs or domains of thedifferent websites that are to be retrieved. Alternatively, the websiteretrieval process 220 may be programmed to automatically retrieve a setof Internet websites over a specified interval (e.g., a range ofInternet Protocol (IP) addresses to query). Retrieving a websiteinvolves downloading the content that is associated with the website.This includes downloading the base page that defines the layout andstructure of the website as well as the embedded objects within the basepage. The embedded objects may include text, graphics, advertisements,applications, videos, audio, and scripts as some examples. The embeddedobjects may be retrieved as a result of invoking hyperlinks that arespecified in the base page. In some embodiments, the website retrievalprocess 220 is further tasked with rendering the retrieved websites andperforming any applications or scripts therein, though rendering theretrieved websites may be optionally performed. In some embodiments,HTTP GET requests specifying different URLs or IP addresses are used toretrieve the websites. It is irrelevant what language or languages thewebsite is defined with, as the task of the website retrieval process220 is to retrieve the website regardless of its form or structure.Consequently, the retrieved websites may include HTML, JavaScript,Adobe® Flash, or any other formatting, objects, containers, languages,etc.

Retrieved websites may be stored to memory or a database for subsequentprocessing by the analyzer 230. Alternatively, retrieved websites may bedirectly passed to the analyzer 230 for processing as described in thesection below.

B. Analyzer

In some embodiments, the analyzer 230 is the component of the PEO system210 that computes the credibility scores for the retrieved websites. Todo so, the analyzer 230 obtains a website that has been retrieved by thewebsite retrieval process 220. Next, the analyzer 230 parses the websiteto identify its various elements.

In some embodiments, the analyzer 230 parses a website by identifyingand extracting a set of delimiters (or tags) and their correspondingparameters and attributes. A PEO system administrator may specify theset of delimiters that are to be parsed and how the delimiters are to beclassified based on their parameters and attributes. In someembodiments, specified delimiters that are not present in a retrievedwebsite are ignored and not used in computing a component credibilityscore. In some embodiments, specified delimiters that are not presentedin a retrieved website may impact the overall credibility score of thewebsite and used to identify additions that can be made to the websitein order to bolster its credibility.

Parsing the web site elements includes identifying objects of thewebsite (interactive, executable, visual, or hidden), attributes for theobjects, and other aspects of the website that are derived from theobjects. Some examples of identifiable website elements includegraphics, advertisements, coloring, font, text, hyperlinks, scripts,interactive tools, input fields, number of advertisements, number ofdifferent colors, or any other object that is specified using HTML,JavaScript, ActiveX, Cascading Style Sheets (CSS), XML, and othersimilar languages. These elements can be used to identify the presenceof other objects such as whether a website provides terms and services,clearly presents contact information, identifies the principles ormanagement, clearly presents a refund or shipping policy, etc. It shouldbe apparent that this enumeration is presented for exemplary andexplanatory purposes and is not intended to be limiting. For instance,the analyzer 230 can identify the number of images within a particularwebsite by identifying the number of times the delimiter “<img src=”appears in the website. The analyzer 230 can identify coloring used in awebsite based on the following delimiters as some examples: (1) <FONTCOLOR=“#[six digit hexadecimal value]”>sample text</FONT>, (2) <BODYTEXT=“#[six digit hexadecimal value]”>, and (3) <BODY BGCOLOR=“#[sixdigit hexadecimal value]”>. Parsing of the website elements can also beperformed by rendering the website and using visual scanning techniquesto identify different elements therein. For example, certain elementswithin a website are dynamic and cannot be determined from theassociated delimiters until the associated website code is executed andthe corresponding element is rendered. More specifically, size andorientation of an image may be determined from the delimiters associatedwith the image. However, coloring of the image cannot be determined fromthe delimiters. Coloring may only be determined when the image isrendered and a visual scanning technique is used to analyze the coloringof the rendered image. It should be apparent to one of ordinary skill inthe art that different techniques can be used to parse the websiteelements and therefore, the particular technique that is used isinconsequential. The parsed website elements are temporarily retained inmemory until the website is classified and a set of credibility scoringrules are identified.

The analyzer 230 classifies the website into one or moreclassifications. The classifications are used to identify the set ofcredibility scoring rules to apply to the website in order to computethe component credibility scores and overall credibility score for thatwebsite. As different demographics of users will have different tastesand preferences, the classifications are used to identify credibilityscoring rules for differently classified websites. In other words, theselected set of credibility scoring rules reflect the preferences oridentified subjective factors that the primary demographic of users forthat particular classification of website use to gauge the website'scredibility. In this manner, the credibility of a shopping website iscomputed differently than the credibility of technology news website.The resulting credibility scores therefore allow a website administratorto optimize his/her site for those users that primarily interact withthe website of the administrator. FIGS. 3 and 4 below present differentprocesses 300 and 400 for defining the credibility scoring rules inaccordance with some embodiments.

In some embodiments, the analyzer 230 performs the classification byprocessing content within some of the parsed elements. Specifically,products, services, or certain keywords can be used to perform theclassification. For example, if the words “travel” and “vacation” appearthroughout the content of a first website, the analyzer 230 can classifythe website as one that relates to a first category of “leisure” and asecond category of “services”; if the words “buy”, “Xbox”, and“Playstation” appear throughout the content of a second website, theanalyzer 230 can classify the website as one that relates to a firstcategory of “entertainment”, a second category for “males age 15-40”,and a third category for “e-retailers”. Other website elements fromwhich the website may be classified include the types of advertisementsappearing in the website, references to businesses or persons, thedomain name of the website, and domain names of embedded hyperlinks assome examples. In some embodiments, website classification is performedwith reference to a dictionary that provides a classification based onthe domain names of the websites. Websites can be classified with adesired level of granularity. The examples above illustrate somegradations with which websites can be classified. Because of the variedwebsites in existence today, it will be apparent to one of ordinaryskill in the art that a complete listing for how to classify a websiteis beyond the scope of this discussion.

Based on the determined classifications, the analyzer 230 retrieves aset of credibility scoring rules from the credibility scoring database240. The retrieved set of credibility scoring rules will have beenderived from or are otherwise associated with websites that aresimilarly classified as the retrieved website. Derivation of thecredibility scoring rules is further described with reference to FIGS. 3and 4 below.

The analyzer 230 then matches the parsed website elements to theappropriate credibility scoring rule from the retrieved set ofcredibility scoring rules. This involves providing the appropriateparsed website elements and optionally corresponding attributes of theelements as inputs to the credibility scoring rules. As output, thecredibility scoring rules generate credibility scores, wherein eachcredibility score represents a component credibility score for aparticular aspect or factor of the website that is identified from thewebsite element that is provided as input. Each credibility scoring ruleis encoded with an algorithm that (1) quantifies attributes or featuresof one or more inputted website elements into a score or (2) quantifiesa website element into a score based on the presence or omission of thatelement from the website. The generated credibility scores areassociated back to the website elements that were used as inputs.

In addition to the credibility scores computed for each of the websiteelements, the analyzer 230 also computes an overall credibility score toquantify the credibility of the website as a whole. The overallcredibility score is derived for a website from each of the componentcredibility scores that were computed for that website. Since users areimpacted by some website elements more heavily than others, the analyzer230 may weight different component credibility scores differently whencomputing the overall credibility score for the website. In someembodiments, these weights are associated with the credibility scoringrules when the credibility scores are derived. For example, if aparticular website element is identified by all users in the primarydemographic of users as critically important to the credibility of awebsite, then any component credibility scores that are produced as aresult of credibility scoring rules that accept that website element asinput will be weighted more heavily. The resulting overall credibilityscore for the website is associated with the component credibilityscores and the scores are stored to the credibility score database 250.The association allows for rapid transitioning from the overallcredibility score of a website to its component credibility scores inorder to directly identify those website elements that beneficially ordetrimentally impact the overall credibility score for the website.

In some embodiments, one or more of the component credibility scores arederived from information that is obtained from third party sources wherethe obtained information relates to website credibility. This mayinvolve aggregating user reviews about different websites from aparticular website review site and then quantifying the aggregatedreviews into a component credibility score. In some embodiments,quantifying a review involves adjusting, standardizing, or normalizingthe scale of the review when the review is already some quantifiablemeasure such as a 0 out of 5 rating or ranking. In some embodiments,quantifying a review involves subjecting the review to natural languageprocessing whereby specific words conveying different degrees ofpositivity and negativity are quantified into a component credibilityscore. Other information that can be used to compute a componentcredibility score from a third party source may include Facebook likesfor a particular website. Different credibility scoring rules can beencoded to generate component credibility scores for such information.

C. Credibility Scoring Rules Database

The credibility scoring rules database 240 stores the different sets ofcredibility scoring rules that are used to quantify website elementsinto component credibility scores. The credibility scoring rules aredefined according to at least one of two processes that are describedwith reference to FIGS. 3 and 4 below. However, it should be apparentthat other processes may be used to define other credibility scoringrules.

FIG. 3 presents a first process 300 implementing a judgmental approachto defining credibility scoring rules in accordance with someembodiments. The process 300 begins by identifying (at 310) a sample setof websites that are similarly classified. The sample set of websitesmay be specified by a system administrator or automatically aggregatedusing a set of search results that appear within a search engine whenthe search engine is queried with one or more terms pertaining to thesample set. For example, a sample set of websites that is aggregatedwhen searching for the term “news” includes: www.cnn.com,www.foxnews.com, news.google.com, news.yahoo.com, and www.msnbc.msn.com.

The process presents (at 320) the sample set of websites to a group ofusers that are within the primary demographic of users accessing thesample set of websites. In some embodiments, the websites are presentedas is to the primary demographic of users. In some embodiments, thewebsites are presented with various elements of the websites highlightedor otherwise identified. The highlighting focuses the attention of theusers to those highlighted website elements so that specific feedbackcan be obtained from the users on those elements as opposed to otherelements. To perform the highlighting, the process analyzes each websiteof the sample set of websites to identify elements of interest that arecontained by the websites. The websites may then be presented to theprimary demographic of users with various overlays to highlight theidentified elements of interest. An overlay may include bordering,coloring, or callouts that distinguish the elements of interest fromother elements appearing on the websites. The primary demographic ofusers may be identified based on information obtained from the websitesor may be identified by temporarily monitoring the websites by the PEOsystem. The users may be volunteers or people that are enlisted toformulate the credibility scoring rules for the PEO system. It should beapparent that in some embodiments the sample set of websites does notneed to consist of similarly classified websites and that the group ofusers does not need to include a primary demographic of users for thesampled websites. Instead, the sample set of websites can include anyrandom assortment of websites and the group of users can similarlyinclude any random assortment of users.

The process obtains (at 330) input from the group of users. The inputspecifies whether, in the perception of the users, a presented websiteelement beneficially or detrimentally impacts the credibility of thewebsite and the degree to which the website element impacts thecredibility of the website. More specifically, the input quantifies howan attribute that is selected for that element impacts the credibilityof the website. As an example, the website element may include thebackground coloring of the website and the attribute is the color redthat is used for the background coloring of the website. Users thenquantify the credibility that is associated with the background coloringof the website by specifying a numeric value in a range of numericvalues to represent the credibility contribution for that particularwebsite element. In some embodiments, obtaining (at 330) user inputinvolves providing a questionnaire alongside each of the presentedwebsites in the sample set. The websites and the questionnaire may bepresented in any web browser by having the users direct their webbrowsers to a particular URL (e.g.,credibilityscoring.com/classification24). The questionnaire inconjunction with or independent of the above described highlighting orother overlays may focus on particular website elements such as thecoloring, font, graphics, advertisements, etc. and provide a scale forthe user to rate how they perceive each such element impacting thecredibility of the website. As the user completes the questionnaire fora first website of the sample set of websites, a second website of thesample set of websites is presented with a clean version of thequestionnaire. In some embodiments, the PEO system allows the users tofreely comment on different website elements using a free form inputbox. In addition to rating the element and attribute for the element ofthe presented website, users may be permitted to specify alternateattribute(s) for that element that would improve or degrade credibility.For instance, a user may provide a 5/10 credibility score for the sixadvertisements that appear on a web site and the user may furtherspecify that a credibility score 10/10 would be attainable if there weretwo or fewer advertisements on the website.

From the user inputs, the PEO system develops a knowledgebase of websiteelements and the corresponding attributes of those elements that mostbeneficially and detrimentally impact the credibility of sampledwebsites that are representative of different website classifications.Using the knowledgebase, the PEO system can analyze and compute thecredibility for other websites based on commonality that is sharedbetween the website elements of the other websites and the websiteelements recorded in the knowledgebase. Specifically, the processidentifies (at 340) commonality between the aggregate set of userprovided input. When a sufficient number of users provide similar inputregarding the same website element or the same website, then thatcommonality is encoded into a credibility scoring rule. For example,when at least ten users in the group of users specify a score of threeor lower for a red background color of websiteX and at least ten usersspecify a score of eight or higher for a blue background color ofwebsiteA, then that commonality is encoded into a credibility scoringrule that produces a component credibility score for the backgroundcolor website element of other similarly classified websites. With asufficient sampling, the process is able to determine one or moreattributes that maximize credibility for a specific website element andone or more attributes that minimize credibility for a specific websiteelement with various other attributes in between.

The process encodes (at 350) the identified commonality into one or morecredibility scoring rules. Encoding identified commonality into acredibility scoring rule comprises defining an algorithm that quantifiesone or more website elements, attributes/parameters of a websiteelement, or functionality of a website element into a componentcredibility score where the range of the score is determined from userpreferences. For example, when an attribute for a website element israted a value of 8 on a scale of 0-10 by a majority of users, then otherwebsites having that attribute or a similar attribute will be provided acomponent credibility score of 8. In some embodiments, each credibilityscoring rule is defined to generate a component credibility score on astandardized and/or normalized scale. For example, each credibilityscoring rule can generate a component credibility score ranging in valuefrom 0-10. A credibility scoring rule can be encoded without the usershaving defined scores for each possible attribute. In some suchembodiments, the PEO system requires the specification of an attributefor a high or maximum score and the specification of an attribute for alow or minimum score and the PEO system fills in the remainder of thescores for other attributes based on similarities of the otherattributes to those for which scores have been defined by the users.Extrapolation techniques can be adapted for this role and for fullydefining the range of values for a credibility scoring rule when onlypart of the range of scores have been defined for that credibilityscoring rule.

The credibility scoring rules are associated (at 360) with one or moreparticular classifications such that the credibility scoring rules areused to compute component credibility scores for websites that fallwithin the same classification. In this manner, different sets ofcredibility scoring rules are used to compute component credibilityscores for differently classified websites such that the credibilityscoring rules applied to a particular website are derived from a groupof users that best match the primary demographic of users interfacingwith the particular website. The process stores (at 370) the credibilityscoring rules to the credibility scoring rule database 240 forsubsequent use in computing component credibility scores for similarlyclassified websites. When the credibility scoring rules from thecredibility scoring rule database 240 are used to compute componentcredibility scores and an overall credibility score for a particularwebsite, the scores are associated with the particular website andstored back to the credibility scores database 250.

FIG. 4 presents a second process 400 implementing an empirical approachto defining credibility scoring rules in accordance with someembodiments. The process 400 begins by identifying (at 410) a sample setof known credible and/or non-credible websites that are similarlyclassified. The sample set may be specified by a PEO systemadministrator or based on monitoring a set of similarly classifiedwebsites. For example, a sample set of known credible websites of aparticular classification may be identified based on aggregated positivereviews, website popularity, etc. Stated differently, websites in a setof similarly classified websites that receive the most traffic may bedetermined to be credible and those receiving the least traffic may bedetermined to be non-credible. Other methods may be used to specify thesample set of credible and non-credible websites. A sample set of knowncredible websites classified as news websites may include www.cnn.comand www.foxnews.com.

The process automatedly identifies (at 420) commonality for differentwebsite elements between these known credible and/or non-crediblewebsites. Commonality that is identified between the known crediblewebsites is used to define credibility scoring rules that generate ahigh component credibility score for other websites having similarelements and commonality that is identified between the knownnon-credible websites is used to define credibility scoring rules thatgenerate a low component credibility score for other websites havingsimilar elements. Specifically, when a known credible website contains awebsite element with a particular attribute and another website whosecredibility is being determined contains the same website element withthe same or similar particular attribute, then the component credibilityscore for that website will be similar to that of the known crediblewebsite. Visual scanners or other automated techniques may be employedto automatedly identify the commonality between the different samplesets of websites. In some embodiments, a configuration file specifies alist of website elements to consider and compare. This may includecomparing attributes of different website elements such as the fonts,font sizes, and coloring, and also comparing counts for the number oftimes certain website elements appear such as the number ofadvertisements on a website and the number of links appearing on thewebsite. Other such website elements may be specified and compared.Additionally, manual analysis may be conducted by PEO systemadministrators to identify the commonality.

As with process 300, the process encodes (at 430) the identifiedcommonality into one or more credibility scoring rules. In encoding acredibility scoring rule, the process specifies scores for an attributethat may not be represented in the known credible and known non-crediblewebsites by computing a score based on how closely the attribute matchesto attributes of the known credible and known non-credible websites. Forexample, a sample set of known credible websites are identified to havetwo advertisements on average and a sample set of known non-crediblewebsites are identified to have six advertisements on average such thata credibility scoring rule is encoded to output a credibility score of10/10 for similarly classified websites with two or fewer advertisementsand a credibility score of 0/10 for similarly classified websites withsix or more advertisements. The credibility scoring rule further definesscores for websites having between two and five advertisements. Forexample, a similarly classified website with three advertisements causesthe encoded credibility scoring rule to output a score of 7 on a scaleof 0-10 and a second similarly classified website with fiveadvertisements causes the encoded credibility scoring rule to output ascore of 3 on a scale of 0-10. Therefore, other websites having similarattributes for the website elements of the sample set of known crediblewebsites will receive higher credibility scores than other websites withdissimilar attributes for the website elements.

The credibility scoring rules are associated (at 440) with one or moreparticular classifications and the process stores (at 450) thecredibility scoring rules to the credibility scoring rule database 240for subsequent use in computing component credibility scores forsimilarly classified websites. When the credibility scoring rules fromthe credibility scoring rule database 240 are used to compute componentcredibility scores and an overall credibility score for a particularwebsite, the scores are associated with the particular website andstored back to the credibility scores database 250.

III. Credibility Score Uses

This section details the various uses for the credibility scores thatare computed using the credibility scoring rules and that are stored tothe credibility score database 250. The overall credibility score andeach component credibility score serve various uses depending on whoviews the scores. More specifically, the scores provide differentadvantages to website administrators, users viewing the websites thathave been scored, and search engines that assimilate the scores as partof their results as some examples.

The overall credibility score informs the administrator as to howcredible its website is in comparison to those of its competitors (i.e.,other similarly classified websites). The component credibility scoresthen particularly point out which website elements beneficially impactthe credibility of the website and which website elements detrimentallyimpact the credibility of the website.

FIG. 5 illustrates presenting credibility scores to a particular websiteadministrator in accordance with some embodiments. In this figure, theoverall credibility score 510 for the website and its componentcredibility scores 520, 530, 540, 550, 560, and 570 are overlaid ontothe website. Each credibility score 510-570 is presented with a shorttextual descriptor for specifying the website element that it pertainsto and the corresponding quantified score for that website element. Insome embodiments, each of the credibility scores 510-570 is interactivesuch that the administrator can click on a particular componentcredibility score in order to obtain more information about the score.Such information may include details on how to improve a website elementthat is associated with a particular component credibility score or mayinclude examples of other similar website elements that are quantifiedas highly credible in order to provide direct reference for the websiteadministrator. The detailed information or examples for improving aparticular component credibility score can be obtained from thecredibility scoring rule that was used to score the website element.Specifically, the credibility scoring rule is encoded with one or moreattributes that produce high credibility scores for the website elementand those attributes can be presented by the PEO system to the websiteadministrator for reference.

In some embodiments, the PEO system provides its own website wherebywebsite administrators can search for the credibility scores for theiradministered websites. Specifically, an interface portal of the PEOsystem is accessible at a specific domain name or URL operated by thePEO system (e.g., www.credibiltyscoring.com). Once a web browser isdirected to the PEO system portal, the website administrator can searchfor a specific administered website by specifying the domain name or URLof that website. The PEO system then queries the credibility scoredatabase 550 to retrieve and present the scores to the administrator inthe overlay view of FIG. 5 or via some other presentation. In someembodiments, the PEO system can restrict access to the credibilityscores to only the website administrators of the websites. In some suchembodiments, a website administrator accesses the PEO system portal andlogs in using identifying credentials (e.g., username and password).Using the identifying credentials, the PEO system queries thecredibility score database 250 in order to identify and present thecredibility scores for the website(s) that are administered by thewebsite administrator. In some other embodiments, the credibility scoresfor any website are available to all users.

When the receiving entity is a user, the credibility scores serve toinform the user as to a website's credibility. Users that are lessonline savvy can have a better online experience by using theindependently derived credibility scores of the PEO system to guide themin their online browsing and to help them avoid websites that have beendetermined to be not credible.

FIG. 6 illustrates yet another method of providing credibility scores tousers. In this figure, a toolbar 610 is included within the browserwindow 620. When a website is loaded and displayed in the browser window620, the toolbar 610 automatically queries the credibility scoredatabase 250 to identify one or more credibility scores for thedisplayed website. As the user navigates to different websites, thetoolbar 610 displays the credibility score for that website, therebyensuring that the website is credible or putting the user on notice thatthe website may potentially include non-credible elements. In someembodiments, the toolbar 610 provides additional functionality wherebythe user can obtain more detailed credibility information about awebsite. The toolbar 610 may also be presented in conjunction with theoverlaying of credibility scores.

In some embodiments, the credibility scores are integrated with searchengine results. FIGS. 7 and 8 illustrate two alternatives forintegrating credibility scores into search engine results. FIG. 7illustrates using “mouse-over” functionality to present credibilityscores in accordance with some embodiments. When a user places apointing tool, such as mouse cursor 710, for a specified duration (e.g.,500 milliseconds) over a website link that is part of a search enginequery, an indicator window 720 displays showing the credibility score(s)for that website. To do so, the search engine may associate thecredibility scores with the website links before returning the resultsto the web browser. Alternatively, the search engine results may beintercepted by the PEO system prior to being returned to the webbrowser. The intercepted results are associated with the appropriatecredibility scores and then passed to the web browser. The integrationof the credibility scores with the search engine results allow a user toidentify the credibility of a website prior to accessing that website.In this manner, the user can avoid non-credible websites that arepresented within search engine results.

FIG. 8 illustrates reordering search engine results based on credibilityscores in accordance with some embodiments. This figure illustratesregular search engine results in window 810 and the same set of searchengine results in window 820 that have been reordered based on thecredibility scores that are associated with each of the results.Furthermore, the links for the search results have been appended with acredibility score in window 820. In this manner, users can visualize thequantified credibility score for each of the websites before clicking onor hovering over the links. Moreover, non-credible websites have beenranked lower in the results to discourage users from accessing thosesites.

In some embodiments, partnerships are established between the searchengine and the PEO system to allow the search engine access to thecredibility scores and to allow the search engine to reorder theirresults based on the credibility scores prior to passing the results tothe user. In some embodiments, the PEO system intercepts the searchengine results and reorders the results based on the credibility scoresbefore passing the reordered results to the user. In still someembodiments, the PEO system is integrated with one or more searchengines such that the search engine algorithms automatically account fora website's credibility when determining the website's ranking in a setof results to be returned to a user.

The foregoing has been an exemplary set of website credibility scoreuses. Other uses of credibility scores not explicitly mentioned hereinare nevertheless within the scope of the PEO system and such uses can beapplied by accessing the credibility scores from the credibility scoredatabase 250 of the PEO system.

IV. Computer System

Many of the above-described processes and modules are implemented assoftware processes that are specified as a set of instructions recordedon a non-transitory computer-readable storage medium (also referred toas computer-readable medium). When these instructions are executed byone or more computational element(s) (such as processors or othercomputational elements like ASICs and FPGAs), they cause thecomputational element(s) to perform the actions indicated in theinstructions. Computer and computer system are meant in their broadestsense, and can include any electronic device with a processor includingcellular telephones, smartphones, portable digital assistants, tabletdevices, laptops, desktops, and servers. Examples of computer-readablemedia include, but are not limited to, CD-ROMs, flash drives, RAM chips,hard drives, EPROMs, etc.

FIG. 9 illustrates a computer system with which some embodiments areimplemented. Such a computer system includes various types ofcomputer-readable mediums and interfaces for various other types ofcomputer-readable mediums that implement the various processes, modules,and engines described above (e.g., website retrieval process, analyzer,etc.). Computer system 900 includes a bus 905, a processor 910, a systemmemory 915, a read-only memory 920, a permanent storage device 925,input devices 930, and output devices 935.

The bus 905 collectively represents all system, peripheral, and chipsetbuses that communicatively connect the numerous internal devices of thecomputer system 900. For instance, the bus 905 communicatively connectsthe processor 910 with the read-only memory 920, the system memory 915,and the permanent storage device 925. From these various memory units,the processor 910 retrieves instructions to execute and data to processin order to execute the processes of the invention. The processor 910 isa processing device such as a central processing unit, integratedcircuit, graphical processing unit, etc.

The read-only-memory (ROM) 920 stores static data and instructions thatare needed by the processor 910 and other modules of the computersystem. The permanent storage device 925, on the other hand, is aread-and-write memory device. This device is a non-volatile memory unitthat stores instructions and data even when the computer system 900 isoff. Some embodiments of the invention use a mass-storage device (suchas a magnetic or optical disk and its corresponding disk drive) as thepermanent storage device 925.

Other embodiments use a removable storage device (such as a flash drive)as the permanent storage device. Like the permanent storage device 925,the system memory 915 is a read-and-write memory device. However, unlikethe storage device 925, the system memory is a volatile read-and-writememory, such as random access memory (RAM). The system memory storessome of the instructions and data that the processor needs at runtime.In some embodiments, the processes are stored in the system memory 915,the permanent storage device 925, and/or the read-only memory 920.

The bus 905 also connects to the input and output devices 930 and 935.The input devices enable the user to communicate information and selectcommands to the computer system. The input devices 930 include any of acapacitive touchscreen, resistive touchscreen, any other touchscreentechnology, a trackpad that is part of the computing system 900 orattached as a peripheral, a set of touch sensitive buttons or touchsensitive keys that are used to provide inputs to the computing system900, or any other touch sensing hardware that detects multiple touchesand that is coupled to the computing system 900 or is attached as aperipheral. The input devices 930 also include alphanumeric keypads(including physical keyboards and touchscreen keyboards), pointingdevices (also called “cursor control devices”). The input devices 930also include audio input devices (e.g., microphones, MIDI musicalinstruments, etc.). The output devices 935 display images generated bythe computer system. The output devices include printers and displaydevices, such as cathode ray tubes (CRT) or liquid crystal displays(LCD).

Finally, as shown in FIG. 9, bus 905 also couples computer 900 to anetwork 965 through a network adapter (not shown). In this manner, thecomputer can be a part of a network of computers such as a local areanetwork (“LAN”), a wide area network (“WAN”), or an Intranet, or anetwork of networks, such as the internet. For example, the computer 900may be coupled to a web server (network 965) so that a web browserexecuting on the computer 900 can interact with the web server as a userinteracts with a GUI that operates in the web browser.

As mentioned above, the computer system 900 may include one or more of avariety of different computer-readable media. Some examples of suchcomputer-readable media include RAM, ROM, read-only compact discs(CD-ROM), recordable compact discs (CD-R), rewritable compact discs(CD-RW), read-only digital versatile discs (e.g., DVD-ROM, dual-layerDVD-ROM), a variety of recordable/rewritable DVDs (e.g., DVD-RAM,DVD-RW, DVD+RW, etc.), flash memory (e.g., SD cards, mini-SD cards,micro-SD cards, etc.), magnetic and/or solid state hard drives, ZIP®disks, read-only and recordable blu-ray discs, any other optical ormagnetic media, and floppy disks.

While the invention has been described with reference to numerousspecific details, one of ordinary skill in the art will recognize thatthe invention can be embodied in other specific forms without departingfrom the spirit of the invention. Thus, one of ordinary skill in the artwould understand that the invention is not to be limited by theforegoing illustrative details, but rather is to be defined by theappended claims.

We claim:
 1. A method for computing website credibility, the methodcomprising: with at least one server of a scoring system comprising aprocessor and non-transitory computer-readable memory storinginstructions which when executed by the processor perform: identifying aset of known credible websites from a plurality of websites, whereineach website of the set of known credible websites comprises a similarset of elements; defining a credibility scoring rule for at least aparticular element of the similar set of elements, the credibilityscoring rule quantifying credibility of the particular element based oncommonality between attributes that the set of known credible websitesdefine for the particular element; computing a credibility score usingthe credibility scoring rule for the particular element as defined on anew website that is not in the plurality of websites, wherein the newwebsite defines a particular attribute for the particular element, andwherein computing the credibility score comprises increasing thecredibility score based on each additional web site of the set of knowncredible websites that defines an attribute for the particular elementthat is similar to the particular attribute; and presenting thecredibility score with the particular element of the new website.
 2. Themethod of claim 1 further comprising identifying a set of knownnon-credible websites from the plurality of websites, wherein eachwebsite of the set of known non-credible websites comprises the similarset of elements.
 3. The method of claim 2, wherein computing thecredibility score further comprises decreasing the credibility scorebased on each additional website of the set of known non-crediblewebsites that defines an attribute for the particular element that issimilar to the particular attribute.
 4. The method of claim 2, whereincomputing the credibility scoring using the credibility scoring rule isfurther based on how many websites from the set of known non-crediblewebsites define a similar attribute for the particular element.
 5. Themethod of claim 1, wherein computing the credibility score using thecredibility scoring rule further comprises providing a first score forthe particular element when at least a threshold number of the knowncredible websites defines an attribute for the particular element thatis similar to the particular attribute and providing a second score thatis less than the first score when less than the threshold number of theknown credible websites defines an attribute for the particular elementthat is similar to the particular attribute.
 6. The method of claim 1,wherein identifying the set of known credible websites comprisesidentifying websites from the plurality of websites that exceed aspecified number of visitors.
 7. The method of claim 1 furthercomprising presenting a suggested action with which the credibilityscore for the particular element of new website can be improved.
 8. Themethod of claim 1 further comprising computing a credibility score usingthe credibility scoring rule for the particular element as defined oneach of a plurality of new websites.
 9. The method of claim 8 furthercomprising reordering results of a search engine query based on thecredibility score of each website of the plurality of new websites,wherein reordering the results comprises increasing in the results, arank of a website having a high credibility score and decreasing in theresults, a rank of a website having a low credibility score.
 10. Amethod for scoring website credibility, the method performed by a systemcomprising at least one server with a processor and non-transitorycomputer-readable memory, the method comprising: distinguishing byoperation of the processor, a set of credible websites from a pluralityof websites, each website of the plurality of websites defined in partby a plurality of elements; determining by operation of the processor, arange of attributes that the set of credible websites defines for aparticular element; determining by operation of the processor, a numberof times that each attribute from the range of attributes is defined bythe set of credible websites for the particular element; computing byoperation of the processor, a credibility score for the particularelement of a new website that is not in the set of credible websitesbased on a particular attribute that the new website defines for theparticular element, wherein computing the credibility score comprisesoutputting a credibility score connoting positive credibility when theparticular attribute is similar to an attribute in the range ofattributes and increasing the credibility score based on the number ofthe set of credible websites that define an attribute similar to theparticular attribute; and presenting the credibility score for the newwebsite.
 11. The method of claim 10 further comprising presenting thenew website with the credibility score adjacent to the particularelement.
 12. The method of claim 10, wherein the range of attributes isa first range of attributes, the method further comprising determiningby operation of the processor, a second range of attributes that a setof non-credible websites defines for the particular element.
 13. Themethod of claim 12 further comprising determining by operation of theprocessor, a number of times that each attribute from the second rangeof attributes is defined by the set of non-credible websites for theparticular element.
 14. The method of claim 13, wherein computing thecredibility score further comprises outputting a credibility scoreconnoting negative credibility when the particular attribute is similarto an attribute in the second range of attributes and decreasing thecredibility score based on the number of the set of non-crediblewebsites that define an attribute that is similar to the particularattribute.
 15. A method performed by a credibility scoring systemcomprising at least one server with a processor and non-transitorystorage, the method for assessing website credibility, the methodcomprising: identifying by operation of the processor, a definition thatis specified for each element of a set of elements of a particularwebsite; for each definition that is specified for an element of the setof elements of the particular website, computing a credibility scorebased on commonality with definitions that a set of credible websitesspecify for the element; and presenting from the credibility scoringsystem, credibility of the particular website by presenting acredibility score for each element of the set of elements of theparticular website, each credibility score quantifying an impact that aparticular element has on overall credibility of the particular website.16. The method of claim 15, wherein computing the credibility score isfurther based on a number of the set of credible websites that specify asimilar definition to the definition that is specified for acorresponding element of the particular website.
 17. The method of claim15, wherein computing the credibility score comprises increasing thecredibility score for a particular element of the set of elements foreach additional website of the set of credible websites that defines asimilar definition to the definition that is specified for theparticular element of the particular website.
 18. The method of claim 15further comprising computing an overall credibility score for theparticular website based in part on each credibility score that iscomputed for each element of the set of elements of the particularwebsite.
 19. The method of claim 18 further comprising presenting theoverall credibility score in conjunction with presenting the credibilityof the particular website.